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A Partial Pre-aggregation Scheme for HOLAP Engines

机译:Holap发动机的部分预聚合方案

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This paper describes a scheme for partial pre-aggregation to speed up the response time of queries that are posed for the array-like interface, subject to the constraint that all pre-computed aggregates must fit into storage of a predetermined size. The target query workload consists of all base and aggregate cells that are stored in a multidimensional array (i.e. cube). These queries are actually range queries pre-defined by users. Due to the huge size of all possible aggregate cells, the emphasis of our scheme is to reduce the overhead for query compilation. An efficient and effective query decomposition method is devised, which works well with a pre-aggregation scheme whereby pre-computed aggregates form a sub-cube of the full cube. A greedy algorithm is devised is to derive such a sub-cube. A HOLAP engine which implements this partial pre-aggregation scheme is described. Experimental results using both synthetic and real-life datasets are presented to demonstrate that the partial pre-aggregation scheme is viable, and for some complex queries, accelerates query execution by close to 300 times.
机译:本文介绍了用于部分预聚合的方案,以加速为阵列类似的界面构成的查询的响应时间,受到所有预先计算的聚合必须适合于存储预定大小的约束。目标查询工作负载包括存储在多维数组(即立方体)中的所有基础和聚合单元格组成。这些查询实际上是用户预定义的范围查询。由于所有可能的聚合单元的巨大尺寸,我们的方案的重点是减少查询编译的开销。设计了一种有效且有效的查询分解方法,它适用于预聚合方案,其中预先计算的聚合形成了完整立方体的子立方体。设计了一种贪婪的算法是导出这样的子立方体。描述了一种实现这种部分预聚合方案的HOLAP引擎。使用合成和现实生活数据集的实验结果表明,部分预聚合方案是可行的,并且对于一些复杂的查询,通过接近300次加速查询执行。

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